Conventionally, many sensing devices of these types have been suggested. For example, an apparatus employing an optical method described below is known. Light emitted from a photo emission element is introduced to a transparent plate, reflected by a sensing surface of the transparent plate, and then received by a photo-detector, thereby detecting raindrops. In other words, when water or the like exists on the sensing surface, the reflection condition of this surface changes, so that light quantity entering the photo-detector decreases. A conventional object sensor senses an object by recognizing this change.
Conventionally, such recognition of changes often has been made by comparison with a reference value (for example, JP 10-186059 A (1998)).
Since these rain sensing devices are used under various conditions in practice, counter measures have to be taken to prevent their malfunction. Foe example, a plurality of reference values are set according to various modes (see JP 10-186059 A (1998)), or the reference value is replaced and updated sequentially (see JP 2-68248 A (1990)).
In these raindrop sensing devices described above, the logic of sensing raindrops has become more complex, thus making it difficult to process the detection judgement at a high speed. Furthermore, all these methods basically judge the condition of the sensing surfaces and detect raindrops by comparison with the reference values. Therefore, owing to an influence of external light and conditions of the sensing surface such as dirt, it has been difficult to prevent the malfunction.
Moreover, in general rain sensing devices for vehicles, the size of the sensing surface is much smaller than that of the region to be wiped. Even though there is a relatively low probability that a particular raindrop will drop on such a small area, identifying certain features of the raindrop may allow the rain condition to be estimated. This makes it possible to control the wiper appropriately according to the rain condition. For this purpose, it is necessary to recognize the rain conditions by detecting the size of the sensed raindrops or the like.
For example, some kind of image processing based on data of a windshield glass would make it possible to recognize and identify the rain conditions. Realizing such an image processing requires expensive hardware resources such as a powerful CPU and a large amount of memory. However, in many cases, the hardware of the rain sensing devices to be mounted on vehicles needs to be inexpensive to meet the requirements of affordable costs and the like.